Targeting television advertisements based on automatic optimization of demographic information

ABSTRACT

Systems and procedures which allow for the placement of advertisements in an optimized manner are presented. Systems may be provided which may be configured to optimize a media plan (either automatically or manually, or a combinations of both) using demographic vectors, and may display the optimization results in a quantifiable manner using terms and numbers.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Ser. No.61/183,928 filed Jun. 3, 2009, the entire disclosure of which isincorporated by reference herein.

FIELD OF INVENTION

The invention generally relates to video processing, and morespecifically to optimization of the placement of advertisements in videoprogramming.

BACKGROUND

Purchasers of advertising space, for example television advertisements,typically place advertisements according to a media plan. Media buyersattempt to place advertisements based on fairly broad demographics, suchas gender, age, employment, income or other definable group. Theydevelop media plans to place their commercials in TV inventory to reacha certain (preferably high) portion of their target demographics.

A media buyer may have one or more products or brands, with associatedtarget demographics, as well as a set of goals for this specificcampaign/plan. Goals are typically expressed as a combination of budget($ cost) and a certain reach. The buyer then will try to meet, or get asclose as possible to, the reach goal while attempting to stay withinbudget. The buyer will look at ratings data, inventory pricing, androtations, and will try to come up with the optimal allocation ofinventory against the goals. Buyers may perform this process for asingle product with a single spot, or for a single product with multiplespots (with different target demo audiences for example), or formultiple products (each with one or more spots), or even for multipleadvertisers (with one or more spots each). Such buyers may buy largefootprints (for example national, or regional distribution) and may notbe able to differentiate within the footprint (the only way to fine-tunemultiple spots to target demographics may be through managingrotations).

What is needed, therefore, is a system and method to allow for optimizedtargeting of advertisements in order to produce and demonstrate a betteryield.

SUMMARY

Embodiments of the present invention may provide for systems andprocedures which allow for the placement of advertisements in anoptimized manner. In some examples, systems are provided which may beconfigured to optimize a media plan (either automatically or manually,or a combination of both), and may display the optimization results in aquantifiable manner using terms and numbers.

According to one embodiment of the invention, a computer-implementedmethod for optimizing targeted media is presented. A processor defines auniverse, including a plurality of media targets, for delivering mediacontent on a network. For each media target, the processor defines atleast one demographic vector, where each demographic vector contains aplurality of indices and each index represents an attribute score. Thedemographic vector is stored in a memory device and the processoroptimizes a rotation of media content to the universe by determining theappropriate placement of the media content in each of the media targetsbased on the attribute scores in the demographic vector.

According to another embodiment of the system, a computer programproduct including a computer usable medium having control logic storedtherein causes the computer to optimize the targeting of media. Thecontrol logic includes a first computer readable program code means forcausing the computer to define a universe for delivering media contenton a network, where the universe contains a plurality of media targets.A second computer readable program code means causes the computer to,for each media target, define at least one demographic vector, eachdemographic vector having a plurality of indices and each indexrepresents an attribute score. A third computer readable program codemeans causes the computer to store the demographic vector in a memorydevice and a fourth computer readable program code means causes thecomputer to optimize a rotation of media content to the universe bydetermining the appropriate placement of media content in each of themedia targets based on the attribute scores in the demographic vector.

Yet another embodiment of the invention includes a computer-implementedmethod for optimizing targeted media. The computer includes a processor,a memory device and control logic stored therein. The processor definesa universe for delivering media content on a network, where the universecontains a plurality of media targets. For each media target, theprocessor defines at least one demographic vector, each demographicvector including a plurality of indices and each index represents anattribute score. The demographic vector is stored in the memory deviceand the processor optimizes a rotation of media content to the universeby determining the appropriate placement of media content in each of themedia targets based on the attribute scores in the demographic vector.The control logic defines a goal, defined by a parameter to beaccomplished by delivery of the media content and optimizes the rotationof media content subject to the parameter of the goal. An indicatorrepresenting the effectiveness of the rotation in accomplishing the goalis displayed to a user through an interface.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be more readily understood from a detaileddescription of the preferred embodiments taken in conjunction with thefollowing figures:

FIG. 1 illustrates an example interface screen in accordance with anexample embodiment of the present invention;

FIG. 2 illustrates an example interface screen in accordance with anexample embodiment of the present invention;

FIG. 3 illustrates an example interface screen in accordance with anexample embodiment of the present invention;

FIG. 4 illustrates an example interface screen in accordance with anexample embodiment of the present invention;

FIG. 5 illustrates an example interface screen in accordance with anexample embodiment of the present invention; and

FIG. 6 depicts some of the steps of a method of optimization inaccordance with an embodiment of the invention.

DETAILED DESCRIPTION

Throughout the application, where compositions are described as having,including, or comprising specific components, or where processes aredescribed as having, including or comprising specific process steps, itis contemplated that compositions of the present teachings also consistessentially of, or consist of, the recited components, and that theprocesses of the present teachings also consist essentially of, orconsist of, the recited process steps.

In the application, where an element or component is said to be includedin and/or selected from a list of recited elements or components, itshould be understood that the element or component can be any one of therecited elements or components and can be selected from a groupconsisting of two or more of the recited elements or components.Further, it should be understood that elements and/or features of acomposition, an apparatus, or a method described herein can be combinedin a variety of ways without departing from the spirit and scope of thepresent teachings, whether explicit or implicit herein.

The use of the terms “include,” “includes,” “including,” “have,” “has,”or “having” should be generally understood as open-ended andnon-limiting unless specifically stated otherwise.

The use of the singular herein includes the plural (and vice versa)unless specifically stated otherwise. Moreover, the singular forms “a,”“an,” and “the” include plural forms unless the context clearly dictatesotherwise. In addition, where the use of the term “about” is before aquantitative value, the present teachings also include the specificquantitative value itself, unless specifically stated otherwise. As usedherein, the term “about” refers to a ±10% variation from the nominalvalue.

It should be understood that the order of steps or order for performingcertain actions is immaterial so long as the present teachings remainoperable. Moreover, two or more steps or actions may be conductedsimultaneously.

Example embodiments of the present invention provide systems and methodswhich may optimize the placement of advertisements in televisionprogramming. It is noted that the embodiments described below makereference to television systems, and television commercials andadvertisements. It is to be understood that the present invention is notlimited to such embodiments however, and that other embodiments relateto other media types, such as radio, streaming video or any other mediadistribution system, as well as to the insertion of other kinds ofmessages.

Embodiments of the present invention may provide systems which optimizethe placement of advertising. Such a system may be configured to placemedia within a universe of inventory. That universe may be made up of aset of physical targets (T_(i)). For instance, the universe could be anational cable network or other definable network of media contentrecipients. Physical targets, for example, may be individual digitalcable subscribing homes, individual set-top boxes or other end-points ofa media transmission. Targets could also include ad-insertion zones,physical regions, programs, periods of the day, real-time conditionals,or any other definable.

Embodiments of the invention may also be configured with demographicinformation relating to each of the physical targets. Such informationmay be stored in any convenient form such as a database, table, or othersuitable memory structure on a storage device. As an example, a systemmay store a set of detailed demographic vectors (S) for each individualphysical target (T), where each demographic vector (S_(i)) represents aspecific population segment. The population segments, may include, forexample and without limitation, income level, gender, number ofresidents in a household, age ranges, employment, education levels,real-time conditionals (such as weather, news, stock markets) or anyother definable demographic. According to one embodiment demographicvector data may be obtained in real-time from third-party sources suchas wire services, news outlets, Internet sites, web pages, or otherservice providers.

In an illustrative demographic vector, each index represents a specificvalue, or attribute score, within the segment (for example income rangessuch as: “less-than $40 k”, “$40 k-$60 k”, “$60 k-$80 k”, “$80 k-$100k”, “greater-than $100 k”). The values of the attribute score within thevector represent how the associated target (T) scores against thesesegment values. For example, an ad-insertion zone could have a vectorfor the “family size” segment that is represented as follows:

$\begin{matrix}{{S_{0801,{Family\_ Size}}\begin{pmatrix}{{single\_ no}{\_ kids}} \\{{single\_ with}{\_ kids}} \\{{couple\_ no}{\_ kids}} \\{{couple\_ with}{\_ kids}}\end{pmatrix}} = \begin{pmatrix}301 \\12 \\178 \\739\end{pmatrix}} & (1)\end{matrix}$

The above example vector would indicate that the particular zone has arelatively high density of couples with children, and a very low densityof single parents with kids (the values in the example are indexedbetween 0 and 1000). In another example, a physical target may representa particular household, and may be associated with a vector indicatingthe propensity to purchase a particular type of automobile:

$\begin{matrix}{{S_{X,{Propensity\_ Car}}\begin{pmatrix}{sedan} \\{sports} \\{minivan} \\{SUV} \\{truck}\end{pmatrix}} = \begin{pmatrix}221 \\98 \\897 \\556 \\131\end{pmatrix}} & (2)\end{matrix}$Such a vector would indicate that the household is likely to buy aminivan or an SUV with a much smaller likelihood of purchasing a sportscar or truck. Again, the values in this embodiment may be indexed,between 0 and 1000).

Example systems may provide and store any number of such vectorsassociated with the physical targets stored. Each physical target may beassociated with any number of demographic vectors. In exampleembodiments, each vector may have a defined set of indices, and adefined range of values. The values need not necessarily be normalized.For example, some example demographic vectors may comprise binaryvalues. The following example shows a vector for household X indicatingthe number of children in the household:

$\begin{matrix}{{S_{X,{{Nr\_ of}{\_ Kids}}}\begin{pmatrix}{none} \\{one} \\{two} \\{three} \\{{four} +}\end{pmatrix}} = \begin{pmatrix}0 \\0 \\1 \\0 \\0\end{pmatrix}} & (3)\end{matrix}$

According to this vector, household X has two (2) children. As theexample illustrates, there may be restrictions to the values a vectormay take. In this embodiment, because the household cannot have twodiscrete numbers representing the number of children in the household,only one value can be 1, while the others must be 0; therefore allvalues always add up to 1. Example systems may define and store any suchrestrictions on particular vector definitions.

Thus embodiments of the system may be configured with a physicaluniverse (U) that comprises a number of physical targets (T):

$\begin{matrix}{U = {\sum\limits_{i}T_{i}}} & (4)\end{matrix}$

Where every target T_(i) is defined by a defined set of vectors (S):

$\begin{matrix}{T_{i} = {\sum\limits_{j}S_{i,j}}} & (5)\end{matrix}$

Where each vector (S) defines scores against segmentation values:

$\begin{matrix}{S_{i,j} = \begin{pmatrix}x_{1} \\x_{2} \\x_{3} \\\ldots \\x_{n}\end{pmatrix}} & (6)\end{matrix}$

Each of the demographic vectors may be summed, multiplied or optimizedany another manner to determine the most effective media content foreach individual defined target. The rotations of media contentdistributed over the universe may then be customized, by target, togenerate the most effective results.

Embodiments of the system may also provide for the configuration of amedia plan or campaign. For example, a media plan which may covermultiple brands, or products, each of which may have a distinct targetdemographic, budgets, and reach goals. “Reach” as used herein, refers tothe number, or percentage, of the target demographic group that will beexposed to the media plan. Each brand may have a set of targetdemographics associated with it. Example systems may allow advertisersto enter and store such demographics. Such target demographics may bemore detailed than the typical television buying demographic. Forexample a target demographic may be defined as “males 18-25” instead ofthe more generic “males 18-45,” which is a typical demographic used inthe television industry.

In addition systems may allow for the configuration of a set of goals.Goals can be set in terms of many parameters including, but not limitedto, budget per product/brand, desired reach, flight (“flight” as usedherein refers to the dates when the media plan is scheduled to beon-air), frequency (“frequency” as used herein refers to the averagenumber of times a person is exposed to the media plan), or a frequencycap, which imposes an upper bound on the frequency.

Other example parameters by which a media plan may be defined mayinclude Cost-Per-Mille (CPM) which expresses the cost of reachingabsolute numbers of viewers. The CPM, according to one embodiment, isthe cost to reach 1000 people. Similarly, the Targeted CPM (TCPM) mayalso be used which is the cost to reach 1000 people in the target demo.It is calculated, according to one embodiment, as TCPM=CPM/“fraction,”where “fraction” represents the fraction of the total universe that isactually in the target demo. Therefore, if the CPM for a particularmedia plan is $50 and half of the viewers are male (fraction=0.5), thenthe TCPM would be $100 (=$50/0.5).

Other goal parameters may be defined in terms of rating points. A ratingpoint refers to one percentage point of the target demographic. Forexample, if a media plan is targeted at males, and it consists of 10insertions into programs that each have a rating of 5 for males (meaningthat an average of 5% of the male population will watch these programs),then this plan would deliver 50 (=10×5) Gross Rating Points (GRPs),which may be used as a goal parameter in some embodiments. Anotherparameter which may be used is Cost-Per-Point (CPP) which refers to thecost to deliver one rating point. So if the example media plan wouldcost $10,000 then the Cost-Per-Point (CPP) would be $200 (=$10,000/50).Ratings are dependent on programs and parts of the day, such as MorningNews (5:00 am-9:00 am), evening news, primetime, or other definableperiod. Such parameters are not exhaustive, and any other quantifiableparameters may be used.

Embodiments of the invention may also provide a processor configured tooptimize the media plan. For instance, example systems may use thedifference in demographic vectors per zone, or other physical target,described above, to calculate the optimal rotation as to that zone,driven by the goals of the media plan. One embodiment of the system mayperform optimization automatically, for example, as soon as thetargeting screens are initially opened, or when a user selects an“Auto-Optimization” button. In addition, example systems may allow usersto manually override and refine the media placement. In both cases,example systems may show (for each spot/product/brand) the Targeted CPM,or other target value, at any given time, providing instant feedback onthe value that is being added by the optimization system.

Example systems may optimize placements based on any number of definedgoals as described above. For instance, a system may be configured tooptimize placement according to reach or CPM. In addition, examplesystems may allow for optimization based on multiple parameters at once.For instance, a system may be configured to optimize placement based onreach, but may do so only with a defined budget goal. Thus, the systemmay attempt to come as close as possible to maximizing reach, while notexceeding the limit set by the budget goal. Any combination ofparameters may be used to guide optimization, and multiple parametersmay be combined in any logical manner according to any reasonableformula or set of priorities.

In one example system the targeting universe may be divided into zones,and there may be a defined, fixed set of vectors per zone (definitionsand data are pre-loaded in tables and are not configurable). Inaddition, the system may be configured with a fixed media plan (againpre-loaded and not configurable). All data may be aggregated data at thezone level. The system may allow users to configure multiple advertiserswith one spot each, or one advertiser with multiple products/brands withone spot per product/brand. In addition, the optimization goals may beconfigured in terms of budgets per client/product as well as reach. Thusthe system may maximize reach (i.e., come as close as possible to allgoals) against fixed budgets.

Illustrative embodiments may also provide user interfaces which allowusers to configure the system for various spots/products/brands. Forinstance, FIG. 1 illustrates an interface which may be provided by anexample system allowing users to associate spots with particulardemographic groups. The interface displays the spots which have beendefined 100 and also displays a number of target demographic groups 110with which the spots may be associated. Note that the demographic groupsmay be represented by labels which may be more specifically defined(e.g., income less-than $50,000, etc.). In addition, the interface mayallow a user to build associations between the spots and targetdemographics by checking a box 120.

FIG. 2 illustrates another example screen from an interface. The screendisplays information allowing a user to see the current rotation as toeach demographic. For instance, the screen again shows advertisementspots 200, and demographic groups 210. Here, however, the interfaceprovides percentages illustrating how each spot is placed within thedemographic group 220. For instance, two spots target the “UrbanMarrieds” group equally in the example.

FIG. 3 shows another example interface screen. FIG. 3 again illustratesa number of spots 300. Here, however, the spots are shown divided overphysical zones to which the advertisements themselves are targeted 310.For instance, the example screen shows the zones in a Chicago cablenetwork 310. The exemplary screen illustrates how spots are targetedwithin each zone 320. For instance, as seen in the first row of theinterface screen, three spots are targeting zone number 0573.

Such a system may also include an interface which may displayinformation indicating the effects of the optimization. For example, theinterface may show Targeted CPMs, which may be calculated by the system.FIG. 4 illustrates an embodiment of a conceptual interface screen,similar to the other example screens of FIGS. 1-3, with three additionalfields for each spot. The system may dynamically compute the fields andupdate them after every change. The screen in FIG. 4 illustratesproviding <nat_TCPM> 400, which refers to the Targeted CPM that can beaccomplished for each spot in a certain media-buy based on an optimalnational rotation. The example screen also provides a <opt_TCPM> field410, which refers to the optimized Targeted CPM that can be accomplishedwhen the rotations are optimized on the individual zones or syscodes.Typically, opt_TCPM is greater than nat_TCPM. In a worst case scenario,running the national rotation in every zone/syscode would result in thenational TCPM being exactly the same as the individual zone TCPM). Theexample screen also provides a <yield> field 420, which refers to thepercentage increase/decrease between <opt_TCPM> and <nat_TCPM>,according to one embodiment. If <opt_TCPM> is smaller than <nat_TCPM>this number should be positive (and may be shown in green to reflect apositive comparison). If <opt_TCPM> is bigger than <nat_TCPM> then thisnumber should be negative (and may be shown in red).

FIG. 5 illustrates one embodiment of the invention using such aninterface. In FIG. 5, the screen displays a set of products 500(Snickers, Twix, Uncle Ben's, Pedigree and Whiskas) and a set ofdemographic segments 510 (segment 1-segment 5). The screen shows thecurrent rotation for each segment 520, determined by the system using anoptimization process described above. In addition, for each product, thescreen shows the additional fields discussed above. For instance, forthe Snickers product, the screen shows the national TCPM as $35 and theoptimized TCPM at $27 for a yield of +23%.

Other embodiments of systems may be configured differently as differentmedia buyers may work in different ways. For instance, some buyers mayaggregate the CPM over all brands and inventory, so that everybody paysthe same flat fee, in which case the system may be configured to showGRPs instead of TCPMs. Systems may be configured with a list ofindicators to choose from, for example, National Targeted CPM (TCPM incase of a nationally executed plan), Optimized Targeted CPM (TCP in caseof a locally executed/optimized plan), National GRP (GRP in case of anationally executed plan), Optimized GRP (GRP in case of a locallyexecuted/executed plan), yield, or other quantifiable metrics. Dependingon the products and buyers involved, the system may be configured todisplay different indicators.

Turning now to FIG. 6, a method of optimizing distribution of targetedmedia rotations 600 is depicted. According to one embodiment, a universeis defined 610, the universe made up of media targets. For each mediatarget, demographic vectors are defined 620, as described above. Thesedemographic vectors are then stored 630. According to one embodiment, agoal may be defined 640 reflecting the success of the targeted mediadistribution. The system may optimize the rotation of targeted media 650content based on the demographic vectors or the goal of the targetedrotation. The effectiveness of the rotation is then calculated 660. Ifthe effectiveness of the rotation meets or exceeds the goal 670, therotation may be kept in place. If the results of the rotation areunacceptable, the rotation may be re-optimized 650 to provide betterresults and the effectiveness may be re-calculated 660.

The present invention may be embodied in may different forms, including,but in no way limited to, computer program logic for use with aprocessor (e.g., a microprocessor, microcontroller, digital signalprocessor, or general purpose computer), programmable logic for use witha programmable logic device, (e.g., a Field Programmable Gate Array(FPGA) or other PLD), discrete components, integrated circuitry (e.g.,an Application Specific Integrated Circuit (ASIC)), or any other meansincluding any combination thereof. In a typical embodiment of thepresent invention, predominantly all of the communication between usersand the server is implemented as a set of computer program instructionsthat is converted into a computer executable form, stored as such in acomputer readable medium, and executed by a microprocessor under thecontrol of an operating system.

Computer program logic implementing all or part of the functionalitypreviously described herein may be embodied in various forms, including,but in no way limited to, a source code form, a computer executableform, and various intermediate forms (e.g., forms generated by anassembler, compiler, linker, or locator). Source code may include aseries of computer program instructions implemented in any of variousprogramming languages (e.g., an object code, an assembly language, or ahigh-level language such as Fortran, C, C++, JAVA, or HTML) for use withvarious operating systems or operating environments. The source code maydefine and use various data structures and communication messages. Thesource code may be in a computer executable form (e.g., via aninterpreter), or the source code may be converted (e.g., via atranslator, assembler, or compiler) into a computer executable form.

The computer program may be fixed in any form (e.g., source code form,computer executable form, or an intermediate form) either permanently ortransitorily in a tangible storage medium, such as a semiconductormemory device (e.g., a RAM, ROM, PROM, EEPROM, or Flash-ProgrammableRAM), a magnetic memory device (e.g., a diskette or fixed disk), anoptical memory device (e.g., a CD-ROM), a PC card (e.g., PCMCIA card),or other memory device. The computer program may be fixed in any form ina signal that is transmittable to a computer using any of variouscommunication technologies, including, but in no way limited to, analogtechnologies, digital technologies, optical technologies, wirelesstechnologies (e.g., Bluetooth), networking technologies, andinternetworking technologies. The computer program may be distributed inany form as a removable storage medium with accompanying printed orelectronic documentation (e.g., shrink wrapped software), preloaded witha computer system (e.g., on system ROM or fixed disk), or distributedfrom a server or electronic bulletin board over the communication system(e.g., the Internet or World Wide Web).

Hardware logic (including programmable logic for use with a programmablelogic device) implementing all or part of the functionality previouslydescribed herein may be designed using traditional manual methods, ormay be designed, captured, simulated, or documented electronically usingvarious tools, such as Computer Aided Design (CAD), a hardwaredescription language (e.g., VHDL or AHDL), or a PLD programming language(e.g., PALASM, ABEL, or CUPL).

Programmable logic may be fixed either permanently or transitorily in atangible storage medium, such as a semiconductor memory device (e.g., aRAM, ROM, PROM, EEPROM, or Flash-Programmable RAM), a magnetic memorydevice (e.g., a diskette or fixed disk), an optical memory device (e.g.,a CD-ROM), or other memory device. The programmable logic may be fixedin a signal that is transmittable to a computer using any of variouscommunication technologies, including, but in no way limited to, analogtechnologies, digital technologies, optical technologies, wirelesstechnologies (e.g., Bluetooth), networking technologies, andinternetworking technologies. The programmable logic may be distributedas a removable storage medium with accompanying printed or electronicdocumentation (e.g., shrink wrapped software), preloaded with a computersystem (e.g., on system ROM or fixed disk), or distributed from a serveror electronic bulletin board over the communication system (e.g., theInternet or World Wide Web).

It will further be appreciated that the above-described methods andprocedures may be provided using the systems disclosed herein, or onother types of systems. The methods and procedures, unless expresslylimited, are not intended to be read to require particular actors orsystems performing particular elements of the methods.

In the preceding specification, the present invention has been describedwith reference to specific example embodiments thereof. It will,however, be evident that various modifications and changes may be madethereunto without departing from the broader spirit and scope of thepresent invention. The description and drawings are accordingly to beregarded in an illustrative rather than restrictive sense.

What is claimed is:
 1. A method comprising: receiving first informationcomprising demographic data associated with a plurality of zones;determining, based on the demographic data, a plurality of demographicvectors associated with a plurality of population segments within theplurality of zones; determining, based on the plurality of demographicvectors and based on a targeted reach for first media content, a firstrotation of the first media content within the plurality of zones;causing, via a user interface, display of second information associatedwith placement of the first media content during the first rotation,wherein the user interface comprises at least a national targetedcost-per-mille (CPM) field and an optimized CPM field, and wherein thesecond information indicates a yield percentage increase or decrease forthe national targeted CPM field and the optimized CPM field; anddetermining, based on the second information, a second rotation ofsecond media content.
 2. The method of claim 1, wherein the firstrotation is further determined based on budget, flight, frequency,frequency cap, cost-per-mille, targeted cost per-mille, gross ratingpoints, or cost-per-point.
 3. The method of claim 1, wherein the firstinformation is received from one or more web content sources, whereinthe one or more web content sources is associated with at least one of awire service, media service, news outlet, or website.
 4. The method ofclaim 1, wherein each demographic vector of the plurality of demographicvectors comprises a plurality of indices, wherein each index of theplurality of indices is associated with an attribute score within thepopulation segment, and wherein the attribute score comprises at leastone of a binary value or is indexed between 0 and
 1000. 5. A devicecomprising: one or more processors; and memory storing instructionsthat, when executed by the one or more processors, cause the device to:receive first information comprising demographic data associated with aplurality of zones; determine, based on the demographic data, aplurality of demographic vectors associated with a plurality ofpopulation segments within the plurality of zones; determine, based onthe plurality of demographic vectors and based on a targeted reach forfirst media content, a first rotation of the first media content withinthe plurality of zones; cause, via a user interface, display of secondinformation associated with placement of the first media content duringthe first rotation, wherein the user interface comprises at least anational targeted cost-per-mille (CPM) field and an optimized CPM field,and wherein the second information indicates a yield percentage increaseor decrease for the national targeted CPM field and the optimized CPMfield; and determine, based on the second information, a second rotationof second media content.
 6. The device of claim 5, wherein the firstrotation is further determined based on budget, flight, frequency,frequency cap, cost-per-mille, targeted cost-per-mille, gross ratingpoints, or cost-per-point.
 7. The device of claim 5, wherein the firstinformation is received from one or more web content sources, whereinthe one or more web content sources is associated with at least one of awire service, media service, news outlet, or website.
 8. The device ofclaim 5, wherein each demographic vector of the plurality of demographicvectors comprises a plurality of indices, wherein each index of theplurality of indices is associated with an attribute score within thepopulation segment, and wherein the attribute score comprises at leastone of a binary value or is indexed between 0 and
 1000. 9. Anon-transitory computer-readable storage medium storingcomputer-readable instructions that, when executed by a processor of acomputing device, cause the computing device to perform operationscomprising: receiving first information comprising demographic dataassociated with a plurality of zones; determining, based on thedemographic data, a plurality of demographic vectors associated with aplurality of population segments within the plurality of zones;determining, based on the plurality of demographic vectors and based ona targeted reach for first media content, a first rotation of the firstmedia content within the plurality of zones; causing, via a userinterface, display of second information associated with placement ofthe first media content during the first rotation, wherein the userinterface comprises at least a national targeted cost-per-mille (CPM)field and an optimized CPM field, and wherein the second informationindicates a yield percentage increase or decrease for the nationaltargeted CPM field and the optimized CPM field; and determining, basedon the second, a second rotation of second media content.
 10. Thenon-transitory computer-readable storage medium of claim 9, wherein thefirst rotation is further determined based on budget, flight, frequency,frequency cap, cost-per-mille, targeted cost-per-mille, gross ratingpoints, or cost-per-point.
 11. The non-transitory computer-readablestorage medium of claim 9, wherein the first information is receivedfrom one or more web content sources, wherein the one or more webcontent sources is associated at least one of with a wire service, mediaservice, news outlet, or website.
 12. The non-transitorycomputer-readable storage medium of claim 9, wherein each demographicvector of the plurality of demographic vectors comprises a plurality ofindices, wherein each index of the plurality of indices is associatedwith an attribute score within the population segment, and wherein theattribute score comprises at least one of a binary value or is indexedbetween 0 and
 1000. 13. The method of claim 1, wherein the determiningthe second rotation is in response to at least one of: the yieldpercentage increase or decrease for the national targeted CPM field orthe optimized CPM field being below a threshold.
 14. The method of claim1, wherein the determining, based on the plurality of demographicvectors and based on a targeted reach for first media content, the firstrotation comprises: determining, for each zone of the plurality ofzones, a difference between each demographic vector of the plurality ofdemographic vectors.
 15. The device of claim 5, wherein the determiningthe second rotation is in response to at least one of: the yieldpercentage increase or decrease for the national targeted CPM field orthe optimized CPM field being below a threshold.
 16. The device of claim5, wherein the determining, based on the plurality of demographicvectors and based on a targeted reach for first media content, the firstrotation comprises: determining, for each zone of the plurality ofzones, a difference between each demographic vector of the plurality ofdemographic vectors.
 17. The non-transitory computer-readable storagemedium of claim 9, wherein the determining the second rotation is inresponse to at least one of: the yield percentage increase or decreasefor the national targeted CPM field or the optimized CPM field beingbelow a threshold.